Examples of org.apache.commons.math3.random.MersenneTwister

org.apache.commons.math3.random.MersenneTwister

ath.sci.hiroshima-u.ac.jp/~m-mat/MT/emt.html"> http://www.math.sci.hiroshima-u.ac.jp/~m-mat/MT/emt.html.

This generator is described in a paper by Makoto Matsumoto and Takuji Nishimura in 1998: Mersenne Twister: A 623-Dimensionally Equidistributed Uniform Pseudo-Random Number Generator, ACM Transactions on Modeling and Computer Simulation, Vol. 8, No. 1, January 1998, pp 3--30

This class is mainly a Java port of the 2002-01-26 version of the generator written in C by Makoto Matsumoto and Takuji Nishimura. Here is their original copyright:

Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met:

Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
The names of its contributors may not be used to endorse or promote products derived from this software without specific prior written permission.

THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.

@since 2.0

            int maxEvaluations,
            PointValuePair expected) {
        int dim = startPoint.length;
        // test diagonalOnly = 0 - slow but normally fewer feval#
        CMAESOptimizer optim = new CMAESOptimizer(30000, stopValue, isActive, diagonalOnly,
                                                  0, new MersenneTwister(), false, null);
        final double[] lB = boundaries == null ? null : boundaries[0];
        final double[] uB = boundaries == null ? null : boundaries[1];
        PointValuePair result = boundaries == null ?
            optim.optimize(maxEvaluations, func, goal,
                           new InitialGuess(startPoint),

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    private RandomGenerator generator;


    @Before
    public void setUp() {
        field = new DfpField(40);
        generator = new MersenneTwister(6176597458463500194l);
    }

View Full Code Here


    @Test
    public void testMath864() {
        final CMAESOptimizer optimizer
            = new CMAESOptimizer(30000, 0, true, 10,
                                 0, new MersenneTwister(), false, null);
        final MultivariateFunction fitnessFunction = new MultivariateFunction() {
                public double value(double[] parameters) {
                    final double target = 1;
                    final double error = target - parameters[0];
                    return error * error;

View Full Code Here

     */
    @Test
    public void testFitAccuracyDependsOnBoundary() {
        final CMAESOptimizer optimizer
            = new CMAESOptimizer(30000, 0, true, 10,
                                 0, new MersenneTwister(), false, null);
        final MultivariateFunction fitnessFunction = new MultivariateFunction() {
                public double value(double[] parameters) {
                    final double target = 11.1;
                    final double error = target - parameters[0];
                    return error * error;

View Full Code Here

                        int maxEvaluations,
                        PointValuePair expected) {
        int dim = startPoint.length;
        // test diagonalOnly = 0 - slow but normally fewer feval#
        CMAESOptimizer optim = new CMAESOptimizer(30000, stopValue, isActive, diagonalOnly,
                                                  0, new MersenneTwister(), false, null);
        PointValuePair result = boundaries == null ?
            optim.optimize(new MaxEval(maxEvaluations),
                           new ObjectiveFunction(func),
                           goal,
                           new InitialGuess(startPoint),

View Full Code Here

    private RandomGenerator generator;


    @Before
    public void setUp() {
        field = new DfpField(40);
        generator = new MersenneTwister(6176597458463500194l);
    }

View Full Code Here

            int maxEvaluations,
            PointValuePair expected) {
        int dim = startPoint.length;
        // test diagonalOnly = 0 - slow but normally fewer feval#
        CMAESOptimizer optim = new CMAESOptimizer(30000, stopValue, isActive, diagonalOnly,
                                                  0, new MersenneTwister(), false, null);
        final double[] lB = boundaries == null ? null : boundaries[0];
        final double[] uB = boundaries == null ? null : boundaries[1];
        PointValuePair result = boundaries == null ?
            optim.optimize(maxEvaluations, func, goal,
                           new InitialGuess(startPoint),

View Full Code Here

    }


    @Before
    public void setUp() {
        generator = createConvexHullGenerator(false);
        random = new MersenneTwister(10);
    }

View Full Code Here

 *  - allow editing of the point set
 */
public class GeometryExample {


    public static List<Vector2D> createRandomPoints(int size) {
        RandomGenerator random = new MersenneTwister();


        // create the cloud container
        List<Vector2D> points = new ArrayList<Vector2D>(size);
        // fill the cloud with a random distribution of points
        for (int i = 0; i < size; i++) {
            points.add(new Vector2D(FastMath.round(random.nextDouble() * 400 + 100),
                    FastMath.round(random.nextDouble() * 400 + 100)));
        }
        
        return points;
    }

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                                   new GammaDistribution(5, 1),
                                   new GammaDistribution(9, 0.5));
            container.add(comp, c);


            c.gridx++;
            RandomGenerator rng = new MersenneTwister(0);
            comp = createComponent("Levy", 0, 3,
                                   new String[] { "c=0.5", "c=1", "c=2", "c=4", "c=8" },
                                   new LevyDistribution(rng, 0, 0.5),
                                   new LevyDistribution(rng, 0, 1),
                                   new LevyDistribution(rng, 0, 2),

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org.apache.commons.math3.analysis.differentiation.DerivativeStructure

org.apache.commons.math3.analysis.differentiation.MultivariateDifferentiableVectorFunction

org.apache.commons.math3.analysis.function.HarmonicOscillator

org.apache.commons.math3.analysis.function.Sin

org.apache.commons.math3.analysis.function.Sinc

org.apache.commons.math3.analysis.MultivariateFunction

org.apache.commons.math3.analysis.QuinticFunction

org.apache.commons.math3.analysis.solvers.BrentSolver

org.apache.commons.math3.analysis.UnivariateFunction

org.apache.commons.math3.complex.Complex

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